This document discusses machine learning and how it can be implemented using Firebase MLKit. It begins with basic definitions of machine learning and its differences from traditional programming. It then introduces Firebase as a backend platform and discusses the advantages of performing machine learning on mobile devices for privacy and speed. The document outlines the typical steps to implement machine learning and how Firebase MLKit simplifies this process. It provides examples of machine learning models and capabilities available through Firebase MLKit like text recognition, face detection and image labeling. In the end, it encourages building apps using Firebase MLKit's features.

1. Azzeddine CHENINE
Google Developers Group Algiers, Co-Organizer
Machine Learning
For Mobile Software Engineers
@azzeddineCH_
1

2. Let’s start
with the basics…
Machine Learning, Firebase…

3. Machine Learning…

4. Field of study that gives
Computers the ability to learn
Without being explicitly
Programmed.
Arthur Samuel
Pioneer in Computer Science and AI. Coined the
Term “Machine Learning” in 1959
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5. 🚶
Software Development = Rules
5

6. 🏃
🚶
Software Development = Rules
6

7. 🏃 🚴
Software Development = Rules
🚶
7

8. 🏃 🚴
Software Development = Rules
🚶
8

9. 🚴 🏌
Software Development = Rules
🏃
🚶
9

10. 🚴 🏌
Software Development = Rules
🏃
🚶
10

11. 🚴 🏌
Software Development = Rules
🏃
🚶
Traditional
Programming
Data
Rules
Answers
11

12. 🚴 🏌
Software Development = Rules
🏃
🚶
Machine
Learning
Data
Answers
Rules
12

13. Google Firebase…

14. Firebase
Backend as a service platform
Authentication
Database
Storage
Noti
fi
cation
……
Android. iOS. Web. Unity. C#
Available for
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15. We will move from mobile-
fi
rst to
an AI-
fi
rst world
Google CEO, Sundar Pichai

16. Intersection of the Two Worlds
Machine Learning on Mobile
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17. Intersection of the Two Worlds
Machine Learning on Mobile
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18. Advantages of on device Machine Learning
Speed
Don’t need an
internet connection
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19. Advantages of on device Machine Learning
Privacy
The data don’t have to
leave the device
Speed
Don’t need an
internet connection
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20. Photography…
Easier said than done
Aperture. Shutter speed. ISO.

21. Machine Learning
can sometimes feel the same…

22. Steps to implement Machine Learning
Prepare
Training Data
DevOps
Data scientist
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23. Steps to implement Machine Learning
Prepare
Training Data
Develop
Model
Train, tune,
And evaluate
Model
DevOps
ML expert / Data scientist
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24. Steps to implement Machine Learning
Prepare
Training Data
Develop
Model
Train, tune,
And evaluate
Model
Deploy Model
Developer
DevOps
ML expert / Data scientist
24

25. Steps to implement Machine Learning
Prepare
Training Data
Develop
Model
Train, tune,
And evaluate
Model
Deploy Model Predict
Developer
DevOps
ML expert / Data scientist
25

26. Ml
Life is simple
And so do Firebase MLKit…

27. Steps to implement Machine Learning
With MLKit
DevOps
Select Model from MLKit
Developer
Developer
ML expert / Data scientist
Predict
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28. Developer
Vision Natural Language Costum
Face
detection
Object
detection
Image
labeling
Text
recognition
Barecode
scanning
Landmark
detection
Language
identi

29. fi
cation
Smart reply
On Device
translation
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AutoML

30. Vision Edge
Model
serving
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Face
detection
Object
detection
Image
labeling
Text
recognition
Barecode
scanning
Landmark
detection
Language
identi

31. Build an app with Firebase MLKit

32. Smart real time text recognizer
Build an app with Two features
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Text
recognition

33. Build an app with Two features
Real time face detector and classi
fi
er
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Smart real time text recognizer
Text
recognition
Face
detection

34. References
Android devSummit 2018
Firebase summit 2018
Firebase summit 2019
Google I/O 2019
Firebase website documentation
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35. Thank You
Azzeddine CHENINE
@azzeddineCH_